FRED (economic data)

io.github.mcpwright由 GitHub 帳號 mcpwright 發布v0.1.1更新於 Oct 24, 2026

FRED economic time series + ALFRED vintages: data as originally published, before revisions.

已驗證STDIO僅桌面金融資料與分析

概覽

AI 產生的概覽

唯讀的 FRED 與 ALFRED 經濟時間序列 MCP 伺服器,讓助理搜尋、比較並讀取美國及國際資料,包括當時發布的原始版本。

可以做什麼
  • 以自由文字搜尋序列,並讀取序列的中繼資料與說明
  • 讀取指定日期區間的觀測值(支援轉換與降取樣)、最新值及下次發布日期
  • 將 2 至 5 個序列對齊到同一時間軸比較,並查詢即將發布的資料行事曆
  • 查詢 ALFRED 版本資料:某序列在過去某日的已知狀態、單一資料點的完整修訂歷程,以及序列的修訂日期
適用情境
當助理需要權威的美國及國際經濟資料、發布行事曆,或需要區分最初公布值與現今修訂值時適用,例如分析決策者於某一時點所掌握的數據。
執行需求
以 stdio 在本機執行,通常透過 uvx 啟動 mcpwright-fred 套件,需要 Python/uv 執行環境。需自備免費 FRED API 金鑰,放在 FRED_API_KEY 中;FRED_MCP_USER_AGENT 為選用。需要連線至 FRED API 的網路。
安裝前請注意
FRED API 金鑰依 FRED 使用條款屬於個人金鑰,須自行提供。部分序列由第三方擁有著作權並附帶其條款,超出個人使用範圍時須自行遵守。此伺服器為唯讀,且與聖路易斯聯邦準備銀行無隸屬或背書關係。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 FRED (economic data),將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

fred-mcp

FRED® economic data inside your AI agent — including what the numbers said before the revisions. An MCP server for the Federal Reserve Bank of St. Louis's FRED® API: search and read 800,000+ U.S. and international time series, follow the release calendar, and — the distinctive part — query ALFRED® vintage data: any series exactly as it was known on a past date, and any single data point's full revision history from its initial print to today's value.

Read-only, built on public endpoints, powered by your own free FRED API key. Live API calls with a volatility-aware cache (vintage reads are immutable and cache long; current data stays fresh) — no bulk mirroring.

This product uses the FRED® API but is not endorsed or certified by the Federal Reserve Bank of St. Louis. By using this server you agree to the FRED® API Terms of Use.

Status: v0.1.0 — live on PyPI (uvx mcpwright-fred) and the official MCP Registry (io.github.mcpwright/fred-mcp). 9 tools, CI-gated, built on mcpwright-core.

Why vintage data matters

Economic numbers get revised — sometimes dramatically. The advance estimate of Q4-2008 real GDP told policymakers the economy was shrinking far more slowly than the number that stands today. If an agent reasons about what decision-makers knew at the time using current data, it is quietly wrong. get_series_as_of and get_revision_history make as-published data a first-class question.

Tools

ToolWhat it does
search_seriesFind series IDs by free text, best matches first
get_seriesOne series' full metadata + verbatim notes
get_observationsA date window of values; transforms (pct_change_yoy, …) + downsampling
get_latestThe most recent value + the next scheduled release date
compare_series2–5 series aligned on one date axis
get_release_calendarUpcoming data releases ("when's the next jobs report?")
get_series_as_of ⭐A series exactly as known on a past date (ALFRED vintage)
get_revision_history ⭐One data point's life: initial print → every revision → today
get_vintage_dates ⭐When a series was released/revised; bounds the vintage tools

All tools are read-only and annotated as such.

What can you ask?

Every question below was run live against the real FRED API through these tools (answers as of June 2026 — ask again and they'll be current).

Everyday questions:

  1. "What's the unemployment rate right now, and when's the next jobs report?" — get_latest(UNRATE) → 4.3% (May 2026), next release 2026-07-02.
  2. "What's the 10-year Treasury yield today?" — get_latest(DGS10) → 4.53% (it correctly skips the . rows daily series publish on holidays).
  3. "How has inflation trended over the past year?" — get_observations(CPIAUCSL, transform=pct_change_yoy) → 2.4% → 3.3% → 3.8% → 4.2% over Feb–May 2026.
  4. "Find me data on median household income." — search_series → MEHOINUSA672N (real) and MEHOINUSA646N (nominal), annual.
  5. "Is the labor market loosening? Compare unemployment and job openings since 2024." — compare_series([UNRATE, JTSJOL]) → one aligned table.
  6. "What economic data comes out this week?" — get_release_calendar(7) → 241 release dates, CPI included.
  7. "What was real GDP growth each quarter of 2025?" — get_observations(A191RL1Q225SBEA) → −0.6, +3.8, +4.4, +0.5%.
  8. "Give me CPI as annual averages for the 2020s." — get_observations(CPIAUCSL, frequency=annual) → one row per year.

Questions only the vintage tools can answer:

  1. "How bad did Q4-2008 GDP look to policymakers in early 2009, versus what we know now?" — get_series_as_of(GDPC1, "2009-02-15") → a −3.8% annualized decline as known then (in chained-2000 dollars — the metadata is vintage-pinned too) versus −8.5% in today's data. Policy ran on the first number.
  2. "Was the May 2020 COVID unemployment rate ever revised?" — get_revision_history(UNRATE, "2020-05-01") → first published as 13.3 (2020-06-05), currently 13.2, with each revision dated.
  3. "What mortgage rate did the Fed see going into the March 2022 liftoff meeting?" — get_series_as_of(MORTGAGE30US, "2022-03-16") → 3.85% as known then; 6.48% today.
  4. "How often does GDP actually get revised?" — get_vintage_dates(GDPC1) → 415 vintages since 1991-12-04.

Install

You need a free FRED API key (takes seconds): https://fred.stlouisfed.org/docs/api/api_key_request.html. Keys are personal under the FRED terms — bring your own.

uvx (any MCP client)

json
{  "mcpServers": {    "fred": {      "command": "uvx",      "args": ["mcpwright-fred"],      "env": { "FRED_API_KEY": "your-key-here" }    }  }}

Claude Code

bash
claude mcp add fred -e FRED_API_KEY=your-key-here -- uvx mcpwright-fred

Claude Desktop

Use the one-click .mcpb extension from the latest release (it prompts for your API key), or add the uvx JSON above to your claude_desktop_config.json.

OpenAI Agents SDK / other clients

Any MCP-capable client works — point it at uvx mcpwright-fred over stdio with FRED_API_KEY in the environment.

Notes

  • Revisions: current values often differ from what was originally published; for "what was known at the time", use the vintage tools.
  • Copyrighted series: some FRED series are owned by third parties; their notes carry the owner's terms (surfaced verbatim, flagged via copyrighted). You are responsible for complying with them beyond personal use.
  • Caching & rate limits: responses are cached in-memory (vintage reads long, live reads short) and requests are throttled well under FRED's rate limit. Set FRED_MCP_CACHE=0 to disable caching, FRED_MCP_USER_AGENT to identify your own deployment.

Develop

bash
git clone https://github.com/mcpwright/fred-mcp && cd fred-mcpuv syncuv run pytest                                  # testsuv run mypy                                    # typesuv run ruff check src/ && uv run ruff format --check src/   # lint + formatuv run pre-commit run --all-files              # everything, like CI

Dev loop: feature branch → PR → Code Quality & Tests green → squash-merge.

Roadmap

  • v1 tool surface (9 tools incl. the ALFRED vintage lane)
  • Publish to PyPI (mcpwright-fred) + the MCP Registry
  • Site page at mcpwright.com/fred
  • .mcpb one-click Claude Desktop extension (v0.1.0 release)
  • GeoFRED / maps (pairs with census-mcp)

Questions & feedback

Discussions for questions and ideas · Issues for bugs.


Part of mcpwright — polished MCP servers for authoritative public data · built by Devender Gollapally. FRED® and ALFRED® are registered trademarks of the Federal Reserve Bank of St. Louis. This project is not affiliated with, endorsed, or certified by the Federal Reserve Bank of St. Louis.

來源:README.md,提交 96ed8d6

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.1最新Sep 16, 2026

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